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IJCAI
2007
13 years 5 months ago
Explanation-Based Feature Construction
Choosing good features to represent objects can be crucial to the success of supervised machine learning algorithms. Good high-level features are those that concentrate informatio...
Shiau Hong Lim, Li-Lun Wang, Gerald DeJong
AAAI
1990
13 years 5 months ago
Backward Model Tracing: An Explanation-Based Approach for Reconstructing Student Reasoning
An original methodology, called backward model tracing to model student performance which features a profitable integration of the bug collection and bug construction techniques i...
Danilo Fum, Paolo Giangrandi, Carlo Tasso
IJCAI
1989
13 years 5 months ago
Using and Refining Simplifications: Explanation-Based Learning of Plans in Intractable Domains
This paper describes an explanation-based approach lo learning plans despite a computationally intractable domain theory. In this approach, the system learns an initial plan using...
Steve A. Chien
CVPR
2005
IEEE
14 years 6 months ago
Feature Kernel Functions: Improving SVMs Using High-Level Knowledge
Kernel functions are often cited as a mechanism to encode prior knowledge of a learning task. But it can be difficult to capture prior knowledge effectively. For example, we know ...
Qiang Sun, Gerald DeJong
AAAI
2010
13 years 5 months ago
An Integrated Systems Approach to Explanation-Based Conceptual Change
Understanding conceptual change is an important problem in modeling human cognition and in making integrated AI systems that can learn autonomously. This paper describes a model o...
Scott Friedman, Kenneth D. Forbus